公开(公告)号：US20240331378A1

公开(公告)日：2024-10-03

申请号：US18618134

申请日：2024-03-27

Applicant: Fujitsu Limited

Inventor： Ziqiang SHI ,  Liu LIU ,  Zhongling LIU ,  Rujie LIU

IPC: G06V20/40 ,  G06T7/12 ,  G06T7/13 ,  G06T7/246 ,  G06T7/277 ,  G06V10/26 ,  G06V10/44 ,  G06V10/75

CPC classification number: G06V20/41 ,  G06T7/12 ,  G06T7/13 ,  G06T7/248 ,  G06T7/277 ,  G06V10/26 ,  G06V10/44 ,  G06V10/751 ,  G06V20/49 ,  G06T2207/10016 ,  G06T2207/20132

Abstract: The embodiments of the present disclosure provide an apparatus for identifying items, a method for identifying items and an electronic device. The apparatus includes: a detector configured to detect one or more items in a reference area in one or more image frames in video data; a tracker configured to track an item detected in multiple image frames, wherein multi-hierarchy decision is performed on the item in the multiple image frames by using different time windows; and a classifier configured to identify the item according to a decision result of the tracker. Thereby, even if an item is moved briefly in some scenarios, the item will not be identified as two different items, which can reduce a situation in which the item is identified repeatedly and improve accuracy and robustness of item detection.

公开(公告)号：US20180336438A1

公开(公告)日：2018-11-22

申请号：US15971549

申请日：2018-05-04

Applicant: FUJITSU LIMITED

Inventor： Ziqiang SHI ,  Liu LIU ,  Rujie LIU

IPC: G06K9/62 ,  G06K9/48

CPC classification number: G06K9/6277 ,  G06K9/481 ,  G06K9/6215 ,  G06K9/6256 ,  G06K9/6262 ,  G10L17/00

Abstract: A multi-view vector processing method and a multi-view vector processing device are provided. A multi-view vector x represents an object containing information on at least two non-discrete views. A model of the multi-view vector, where the model includes at least components of: a population mean μ of the multi-view vector, view component of each view of the multi-view vector and noise is established. The population mean μ, parameters of each view component and parameters of the noise , are obtained by using training data of the multi-view vector x. The device includes a processor and a storage medium storing program codes, and the program codes implements the aforementioned method when being executed by the processor.

公开(公告)号：US20180197547A1

公开(公告)日：2018-07-12

申请号：US15866079

申请日：2018-01-09

Applicant: Fujitsu Limited

Inventor： Ziqiang SHI ,  Liu LIU ,  Rujie LIU

IPC: G10L17/18 ,  G10L25/30 ,  G10L17/06 ,  G06F17/17

CPC classification number: G10L17/18 ,  G06F17/17 ,  G10L17/04 ,  G10L17/06 ,  G10L25/30

Abstract: An identity verification method and an identity verification apparatus based on a voiceprint are provided. The identity verification method based on a voiceprint includes: receiving an unknown voice; extracting a voiceprint of the unknown voice using a neural network-based voiceprint extractor which is obtained through pre-training; concatenating the extracted voiceprint with a pre-stored voiceprint to obtain a concatenated voiceprint; and performing judgment on the concatenated voiceprint using a pre-trained classification model, to verify whether the extracted voiceprint and the pre-stored voiceprint are from a same person. With the identity verification method and the identity verification apparatus, a holographic voiceprint of the speaker can be extracted from a short voice segment, such that the verification result is more robust.

公开(公告)号：US20170294191A1

公开(公告)日：2017-10-12

申请号：US15477687

申请日：2017-04-03

Applicant: FUJITSU LIMITED

Inventor： Ziqiang SHI ,  Liu LIU ,  Rujie Liu

IPC: G10L17/02 ,  G10L15/30 ,  G10L17/10 ,  G10L15/22 ,  G10L15/20 ,  G10L17/04

CPC classification number: G10L17/02 ,  G10L15/20 ,  G10L15/22 ,  G10L15/30 ,  G10L17/04 ,  G10L17/10 ,  G10L2015/227

Abstract: The present invention discloses a method for speaker recognition and an apparatus for speaker recognition. The method for speaker recognition comprises: extracting, from a speaker-to-be-recognized corpus, voice characteristics of a speaker to be recognized: obtaining a speaker-to-be-recognized model based on the extracted voice characteristics of the speaker to be recognized, a universal background model UBM reflecting distribution of the voice characteristics in a characteristic space, a gradient universal speaker model GUSM reflecting statistic values of changes of the distribution of the voice characterizes in the characteristic space and a total change matrix reflecting environmental changes; and comparing the speaker-to-be-recognized model with known speaker models, to determine whether or not the speaker to be recognized is one of known speakers.